Data Analytics Consultant

We are looking for a Data Analytics Consultant to lead the design and delivery of modern data engineering and business intelligence solutions for client engagements in Pennsylvania. This Long-term Contract position is ideal for a client-facing consultant who can combine technical architecture expertise with strong communication and consulting skills to guide data strategy, platform design, and analytics adoption. The role will partner with stakeholders across business and technical teams to create scalable data environments, translate complex requirements into practical solutions, and support the continued advancement of enterprise analytics capabilities.

Responsibilities:

• Act as a trusted advisor to clients by evaluating technical options and recommending data and analytics solutions aligned with business goals.
• Architect, build, and launch scalable data platforms across cloud and on-premises environments using modern engineering and business intelligence technologies.
• Lead discovery meetings, stakeholder workshops, and solution presentations to uncover needs and define effective analytics strategies.
• Establish frameworks for data ingestion, transformation, storage, governance, and reporting to support reliable decision-making.
• Develop implementation roadmaps and delivery plans for data initiatives, ensuring technical solutions support long-term business priorities.
• Assess current data ecosystems, identify improvement opportunities, and produce clear architectural documentation and technical recommendations.
• Engage with audiences ranging from executive leadership to delivery teams to explain solution choices, tradeoffs, and expected business impact.
• Contribute across multiple phases of delivery, including consulting, architecture, hands-on development, and pre-sales support when needed.
• Provide deep technical expertise in analytics, data integration, visualization, and modern lakehouse or warehouse design, including security considerations such as row-level access.
• Use tools such as Microsoft Fabric, Azure, Python, Spark, Hadoop, Kafka, SQL, and ETL frameworks to build high-quality analytics and data processing solutions.